Next Article in Journal
A Single-Loop Repetitive Voltage Controller with an Active Damping Control Technique
Next Article in Special Issue
Enhancing Insulating Performances of Presspaper by Introduction of Nanofibrillated Cellulose
Previous Article in Journal
Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach
Previous Article in Special Issue
Study on the Characteristic Decomposition Components of DC SF6-Insulated Equipment under Positive DC Partial Discharge
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Energies 2017, 10(5), 672; doi:10.3390/en10050672

An Elastic Charging Service Fee-Based Load Guiding Strategy for Fast Charging Stations

State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Academic Editor: Issouf Fofana
Received: 18 March 2017 / Revised: 20 April 2017 / Accepted: 2 May 2017 / Published: 11 May 2017
View Full-Text   |   Download PDF [2811 KB, uploaded 17 May 2017]   |  

Abstract

Compared with the traditional slow charging loads, random integration of large scale fast charging loads will exert more serious impacts on the security of power network operation. Besides, to maximize social benefits, effective scheduling strategies guiding fast charging behaviors should be formulated rather than simply increasing infrastructure construction investments on the power grid. This paper first analyzes the charging users’ various responses to an elastic charging service fee, and introduces the index of charging balance degree to a target region by considering the influence of fast charging loads on the power grid. Then, a multi-objective optimization model of the fast charging service fee is constructed, whose service fee can be further optimized by employing a fuzzy programming method. Therefore, both users’ satisfaction degree and the equilibrium of charging loads can be maintained simultaneously by reasonably guiding electric vehicles (EVs) to different fast charging stations. The simulation results demonstrate the effectiveness of the proposed dynamic charging service pricing and the corresponding fast charging load guidance strategy. View Full-Text
Keywords: electric vehicles; fast charging; real-time pricing; charging station selection; navigation strategy electric vehicles; fast charging; real-time pricing; charging station selection; navigation strategy
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Su, S.; Zhao, H.; Zhang, H.; Lin, X. An Elastic Charging Service Fee-Based Load Guiding Strategy for Fast Charging Stations. Energies 2017, 10, 672.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top